资源列表
MATLAB-30-Cases
- 。《MATLAB智能算法30个案例分析》采用案例形式，以智能算法为主线，讲解了遗传算法、免疫算法、退火算法、粒子群算法、鱼群算法、蚁群算法和神经网络算法等最常用的智能算法的MATLAB实现。对广大科研人员有很高的参考价值。-. MATLAB intelligent algorithm 30 case studies, the use of case the main line, the form of an intelligent algorithm to explain the genetic
neutral-networks
- matlab中神经网络算法的应用举例，很容易理解-Examples of the application of neural network algorithm matlab, it is easy to understand
SA
- 模拟退火算法的应用举例，很容易让人理解模拟退火的精髓-Examples of application of simulated annealing algorithm, it is easy to understand the essence of the simulated annealing
SA0-1
- 模拟退火解决0—1背包问题，很好的套用模版-Simulated annealing to solve the 0-1 knapsack problem, apply the template
GA
- 1.遗传算法求解无约束目标函数最大值问题案例分析 2.多约束非线性规划-Genetic Algorithm for Solving the unconstrained maximum objective function of problem cases
fluid_simulation
- 本程序的目的是为了进行无粘性流体的数值计算模拟，通过CFD算法计算每个节点的应力，推算出流体的本构方程-The purpose of this program is to viscous fluid values calculated to simulate the stress the CFD algorithm calculated for each node, calculate the constitutive equation of the fluid
Exameple51Sim
- BP神经网络的仿真，利用工具箱函数进行预测，显示期望值与输出值-BP
car_flow_mass
- 程序的目的是根据行人流的质量、流量守恒方程进行相应的模拟，得到行人的时空序列图，从而有助于解决车辆的拥堵问题-The purpose of the program is based on the quality of the pedestrian flow, the flow conservation equations corresponding analog pedestrian space and time sequence diagrams to help solve the probl
Temperature-fuzzy-control-algorithm
- 温度控制采用模糊控制算法来实现。采用的是C语言-Temperature control by fuzzy control algorithm is proposed to realize. By C language
neural-network-modeling-30-source
- matlab的神经网络建模30个源程序，包括常用的BP，Hopfield，RBF网络的回归-非线性函数回归的实现等-matlab neural network modeling 30 source, including used BP Hopfield RBF network regression- the realization of the nonlinear function regression
ga
- ga算法是利用c语言编写的一个小程序， GA是对问题参数的编码组进行进货,而不是直接对参数本身。-Ga algorithm is to use c language to write a small program
spider
- 机器学习matlab源代码，包括多分类SVM，模式识别，特征选择，回归等算法。-The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with